This Interdisciplinary Training Grant in Biostatistics and Computational Biology proposal from the Harvard School of Public Health (HSPH) is a renewal application that represents an expansion of the existing interdisciplinary training grant in biostatistics at HSPH. It aims at addressing the critical need in the omits era for well-trained quantitative genomic scientists who have a strong understanding of, and commitment to, cutting-edge methodological and collaborative research at the intersection of molecular biology, biostatistics, bioinformatics, computational biology, and genetic epidemiology to analyze, integrate and interpret high- dimensional genomic and environmental data. The training program will involve active participation by over thirty accomplished and experienced multidisciplinary faculty members, including biostatisticians, bioinformaticians and computational biologists, genetic epidemiologists, and molecular biologists with the goal of providing our trainees with experience in all essential elements of this emerging area. The goals of our proposed training program are: * To train high-quality quantitative researchers who have excellent biological, statistical and computational knowledge, and are capable of conducting cutting-edge methodological and collaborative research at the intersection of biostatistics, bioinformatics and computational biology, genetic epidemiology, and molecular biology; * To train quantitative researchers to become strong leaders and effective communicators in an interdisciplinary research environment, and to enable them to conduct translational genomic research from basic sciences to population and clinical sciences focused on developing effective strategies for disease prevention, intervention, and treatments. Trainees will be pre-doctoral students at HSPH in the Departments of Biostatistics and Epidemiology, which will jointly administer the grant. The program proposes initial support of eight students in year 1, and two additional trainees in years 2-5. This training program combines elements of training in both wet labs in biological science and dry labs in biostatistics, computational biology, and genetic epidemiology, accomplished through lab rotations and directed interdisciplinary research that will prepare graduates to become leading quantitative genomic scientists. RELEVANCE: Groundbreaking research and discovery in the life sciences in the 21st century are more interdisciplinary than ever. To expedite scientific advances in the omits era, it is critical to train the next generation of quantitative health science students who are strong in biostatistics, computational biology, molecular biology and genetics epidemiology, and who have enough basic knowledge that they can easily communicate and work with colleagues who have complementary areas of expertise.